Description and Features of a New Computerized Gross Motor Skills Measurement Tool

By Line Tremblay, Moriah Thorpe, Michael Daoust, Céline Larivière, Brahim Chebbi and Valerie Theriault.

Published by Journal of Technologies and Human Usability

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Motor skills, a person’s movement coordination performance quality, are essential to people’s daily functioning (Voelcker-Rehage 2008) and are critical for children’s learning and cognitive development (Miller 1989), perception of academic and athletic self-competence and peer acceptance (for a review see Boudreau-Larivière et al. 2012). Also, levels of gross motor skills competence predict physical activity frequency and intensity in children, (Cairney et al. 2005a; Cairney et al. 2005b), which in turn influence weight status and risk for obesity later in development and during adulthood (Boudreau-Larivière et al. 2012). Therefore, reliable measurements of motor skills are needed to assess whether children’s abilities are within a normal range or show deficits. Classical tests measuring motor skills require that at least one, but preferably two trained evaluators administer the tests by observing a participant performing motor tasks and by making a quick judgment about this participant’s performance. The limit of such methods is that they are prone to errors and misinterpretation by the evaluators (Rosenthal and Rosnow 1991). The objective of this paper is to present and validate a new computerized test using the Kinect technology for motor performance assessment, which has the advantage of registering a participant’s motor skills more precisely than an observer. The computerized test is programmed to assess a participant`s performance using criteria from classical tests.

Keywords: Gross Motor Skills, Computerized Test, Measurement, Assessment

Journal of Technologies and Human Usability, Volume 12, Issue 3-4, December 2016, pp.31-49. Article: Print (Spiral Bound). Article: Electronic (PDF File; 877.167KB).

Dr. Line Tremblay

Professor, School of Human Kinetics, Northern School of Medicine, Laurentian University, Sudbury, Ontario, Canada

Moriah Thorpe

Masters Student, School of Human Kinetics, Laurentian University, Sudbury, Ontario, Canada

Michael Daoust

Student, Math and Computer Sciences Department, Laurentian University, Sudbury, Ontario, Canada

Dr. Céline Larivière

Professor, School of Human Kinetics, Laurentian University, Sudbury, Ontario, Canada

Dr. Brahim Chebbi

Professor, Bharti School of Engineering, Northern Ontario School of Medicine, Laurentian University, Sudbury, Ontario, Canada

Valerie Theriault

Student, Math and Computer Sciences, Laurentian University, Sudbury, Ontario, Canada